🎮 Azure DevOps Guide: 🧠

Create a CI/CD Pipeline for Python application in Azure DevOps with integrate with Azure Repos with pipeline script of deployment and test stages and finally push to Azure Artifacts


🌐 Link: https://github.com/NotHarshhaa/DevOps_Setup-Installations/blob/master/azure-devops/setup-cicd.md

We add daily Tools Setup, Installations, Guides with each and every commands with clear explanation

💎 Now added : Kubernetes, Jenkins, Ansible, AWS, Azure DevOps
More added daily so "fork the repository for updates"


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

Here's your typical Docker Workflow 🐳

If you understand this, you understand enough to accomplish 80% of your Docker tasks.

1⃣ After developing your application, Create a Dockerfile to capture all the assets like code, executables & dependencies.

🔢 Use “docker build” to build an Image from your Dockerfile. You’d normally also use the “--tag” option to give your Image a name & tag (eg- “hello_world:latest”).

🔢 At this point, Docker pulls the Base Image (eg- Alpine, Ubuntu) from a Registry (this is Docker Hub by default). If you’re using a private registry instead, this step might perform authentication as well.

🔢 Run the Container from your newly baked Image using “docker run”. A container goes through various states throughout its lifecycle, depending on the processes running inside it and what you do with it from outside.

🔢 Your image is now ready to be distributed to other users so you “docker push” it to the registry.

🔢 Continuously monitor the performance of your container(s) using "docker stats”. Debug a live container using “docker exec” and “docker inspect”.

🔢 Get back to building 🚀


✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🚨 Everyone says, 'The best way to learn AWS is to build in the cloud.'

BUT...

'How? Where can I get a sample project?' This is the most common question I hear from aspiring and existing cloud engineers.

➡️ Here are 10 handpicked projects you can build for FREE:

➡️ Build a Serverless Web Application: https://lnkd.in/gCgdvmYK

➡️ Create Continuous Delivery Pipeline: https://lnkd.in/gSw_zaVM

➡️ Create and Connect to a MySQL Database with Amazon RDS: https://lnkd.in/gksv8u92

➡️ Amazon EC2 Backup and Restore Using AWS Backup: https://lnkd.in/gxXBasme

➡️ Batch Upload Files to Amazon S3 Using the AWS CLI: https://lnkd.in/gegNihnk

➡️ Deploy a Web App on AWS Amplify: https://lnkd.in/gPdaC65x

➡️ Remotely Run Commands on an EC2 Instance with AWS Systems Manager: https://lnkd.in/gGvd4SZ7

➡️ Detect, Analyze, and Compare Faces with Amazon Recognition: https://lnkd.in/g478VkKm

➡️ Create an Audio Transcript with Amazon Transcribe: https://lnkd.in/gukPRryX

➡️ Analyze insights in text with Amazon Comprehend: https://lnkd.in/gw-miUPm

⛔ SHARE if this was helpful to you - to benefit others ♻️


🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

📌 Complete Prometheus Architecture

You will learn about the following from the Blog.- High Level Prometheus Architecture

➡️ Prometheus Server
➡️ Time-Series Database (TSDB)
➡️ Prometheus Targets
➡️ Prometheus Exporters
➡️ Prometheus Service Discovery
➡️ Prometheus Push Gateway
➡️ Prometheus Client Libraries
➡️ Prometheus Alert Manager
➡️ PromQL

➡️ 𝗗𝗲𝘁𝗮𝗶𝗹𝗲𝗱 𝗕𝗹𝗼𝗴: https://lnkd.in/gVuPeWcS


🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

📌 𝐓𝐡𝐞 𝐦𝐨𝐬𝐭 𝐚𝐬𝐤𝐞𝐝 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬/ 𝐓𝐨𝐩𝐢𝐜𝐬:

𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐯𝐨𝐥𝐮𝐦𝐞𝐬 are an essential feature for managing data in containerized applications. They provide a way to persist and share data between containers within a pod or across pods. Volumes abstract the underlying storage details and make it easier to manage data in a containerized environment.

Some key concepts and implementation details related to Kubernetes volumes:

1️⃣. 𝐓𝐲𝐩𝐞𝐬 𝐨𝐟 𝐕𝐨𝐥𝐮𝐦𝐞𝐬:
Kubernetes supports various types of volumes, each designed for specific use cases. Some common volume types include:
- 𝐄𝐦𝐩𝐭𝐲𝐃𝐢𝐫: An empty directory is created when a pod is scheduled on a node and is deleted when the pod is removed.
- 𝐇𝐨𝐬𝐭𝐏𝐚𝐭𝐡: Uses a directory on the host machine's filesystem and mounts it into the pod.
- 𝐏𝐞𝐫𝐬𝐢𝐬𝐭𝐞𝐧𝐭𝐕𝐨𝐥𝐮𝐦𝐞: Represents a piece of networked storage in the cluster that is provisioned by an administrator and can be dynamically or statically bound to a PersistentVolumeClaim.
- 𝐂𝐨𝐧𝐟𝐢𝐠𝐌𝐚𝐩 𝐚𝐧𝐝 𝐒𝐞𝐜𝐫𝐞𝐭: Special volumes that allow you to inject configuration data or secrets into pods.
- 𝐍𝐅𝐒, 𝐀𝐖𝐒 𝐄𝐁𝐒, 𝐆𝐂𝐄 𝐏𝐃, 𝐚𝐧𝐝 𝐦𝐨𝐫𝐞: Various cloud-specific volume types are also available.

2️⃣. 𝐕𝐨𝐥𝐮𝐦𝐞 𝐋𝐢𝐟𝐞𝐜𝐲𝐜𝐥𝐞:
- When a pod using a volume is created, Kubernetes ensures that the volume is created and mounted.
- When the pod is deleted, the volume is unmounted, and the data is retained for some volume types (like PersistentVolumes) and deleted for others (like EmptyDir).

3️⃣. 𝐃𝐲𝐧𝐚𝐦𝐢𝐜 𝐏𝐫𝐨𝐯𝐢𝐬𝐢𝐨𝐧𝐢𝐧𝐠:
For cloud-based storage solutions and other external storage systems, Kubernetes can dynamically provision volumes when a PersistentVolumeClaim is created. The storage class associated with the PVC defines the storage type and configuration.

4️⃣. 𝐕𝐨𝐥𝐮𝐦𝐞 𝐀𝐜𝐜𝐞𝐬𝐬 𝐌𝐨𝐝𝐞𝐬:
Some volume types support different access modes, such as ReadWriteOnce, ReadOnlyMany, and ReadWriteMany. These modes specify whether the volume can be mounted as read-write or read-only by multiple pods.

5️⃣. 𝐒𝐭𝐚𝐭𝐞𝐟𝐮𝐥𝐒𝐞𝐭𝐬:
For stateful applications, you can use StatefulSets along with PersistentVolumes to ensure stable and unique network identities for pods. This is crucial for databases and other stateful workloads.

6️⃣. 𝐕𝐨𝐥𝐮𝐦𝐞 𝐏𝐥𝐮𝐠𝐢𝐧𝐬 𝐚𝐧𝐝 𝐂𝐒𝐈:
Kubernetes supports custom volume plugins through the Container Storage Interface (CSI). This allows third-party storage providers to integrate with Kubernetes and offer specialized storage solutions.

7️⃣. 𝐏𝐨𝐝-𝐭𝐨-𝐏𝐨𝐝 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧:
Volumes can also be used to share data between different pods within a cluster, enabling inter-pod communication and data sharing.


🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

💼 Hiring Alert 🚨 🚨 for DevOps Engineer 🚨 🚨

📢 Audviklabs, Bangalore, India is hiring !!

We are seeking highly motivated DevOps Engineers.

➡️ Skills - Azure, AWS, GCP, Docker, Kubernetes, CI/CD pipeline Azure DevOps, Python, and Linux.
➡️ Location: Remote
➡️ Number of openings - 7
➡️ Exp . - 2-3 years


Interested??
Please drop your resume at richa.pragya@audviklabs.com

https://harshhaa.hashnode.dev/mastering-aws-devops-tools-your-in-depth-guide-to-streamlining-cloud-operations

Follow 🍩 Like 👍 Share 👍 Comment Your thoughts 💬

🌟 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

☄️ DevOps ♾ Project Ideas for 🌟🌟 💪

1️⃣ Scripting and Automation
Write scripts to automate tasks such as server provisioning, log rotation, or data migration. Use languages like Python or Bash.

2️⃣ Collaborative Git Workflow
Practice collaborative development using Git with a team or by yourself. Set up a Git repository, create branches, and simulate a workflow similar to what you'd experience in a real job.

3️⃣ Dockerize an Application
Containerization is an essential #DevOps practice. Dockerize an application of your choice, create an image, and then deploy it to a container orchestration platform like Docker Swarm.

4️⃣ Container Orchestration with Kubernetes
Learn Kubernetes basics and deploy a simple application on a #Kubernetes cluster. Explore features like pod scaling, rolling updates, and service discovery.

5️⃣ Configuration Management
Use tools like Ansible or Puppet to automate the configuration of multiple servers. Create playbooks or manifests to ensure consistency across your infrastructure.

6️⃣ CI/CD Pipeline for a Web Application
Set up a continuous integration and continuous deployment (CI/CD) pipeline for a simple web application. You can use tools like Jenkins, GitLab CI/CD, or #GitHub Actions. Automate the building, testing, and deployment processes.

7️⃣ Infrastructure as Code (IaC)
Learn and implement Infrastructure as Code using tools like #Terraform or #AWS CloudFormation. Create and manage cloud resources like EC2 instances VPCs in an automated and version-controlled manner.

8️⃣ Monitoring and Alerting Setup
Set up monitoring and alerting for your infrastructure and applications. Use tools like Prometheus and Grafana or a cloud-native solution like AWS CloudWatch. Create alerts for critical metrics.

9️⃣ Log Management and Analysis
Implement a log management system using tools like ELK Stack (Elasticsearch, Logstash, Kibana) or centralized logging on cloud platforms like AWS or Azure. Analyze logs to identify issues and trends.

🔟 Automated Backup and Recovery
Learn how to use a backup service like #Veeam to safeguard your critical data. Ensure that you can quickly recover from data loss or system failures or move your data from one place to another.

1️⃣1️⃣ Multi-Environment Deployment
Set up multiple environments (e.g., development, staging, production) and practice deploying your applications across these environments using automation.

1️⃣2️⃣ Configuration Drift Detection
Implement a system that detects and reports configuration drift in your infrastructure. Tools like AWS Config or custom scripts can help with this.

➡️ Tackle one project at a time.
➡️ Share your wins and lessons on social media.
➡️ Write a blog about your project.
➡️ Ask for help if you need it.

Doing these steps will make you stand out.


🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

Continuous Integration vs Continuous Delivery vs Continuous Deployment


✅ Developers today face increasing demands to deliver software updates and new features at a rapid pace.

Adopting modern development practices like continuous integration (CI), continuous delivery (CD), and continuous deployment can help teams meet these demands and ship software more frequently.

➡️ But what's the difference between these three approaches?

➡️ 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻👇

Continuous integration is the practice of merging developer working copies to shared repositories multiple times per day.

With CI, developers frequently commit their code changes to a shared version control repository.

Each commit triggers an automated build and test process to catch integration errors as early as possible.

CI helps teams avoid "integration hell" that can happen when developers work in isolation for too long before merging their changes.

➡️ 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 👇

Continuous delivery takes CI a step further with automated releases.

CD means that at any point, you can push a button to release the latest app version to users.

The CD pipeline deploys each code change to a testing/staging environment and runs automated tests to confirm the app is production ready.

This ensures developers always have a releasable artifact that has passed tests.

While CD enables releasing often, someone still needs to manually push the button to promote changes to production.

➡️ 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁👇

Continuous deployment fully automates the release process.

Every code commit that passes the automated tests triggers an immediate production deployment.

This enables teams to ship features as fast as developers write code.

However, the business may not want to release daily since this could overwhelm users with constant changes.

Many teams use feature flags so developers can deploy new features, but limit their exposure until the business is ready for the public launch.

Adopting CI, CD, and CD practices can accelerate a team's ability to safely deliver innovation.

The key is automating repetitive processes to limit manual errors, provide rapid feedback, and reduce risk.

This frees up developers to focus their energy on writing great code rather than building and deploying it.
The outcome is faster time-to-market and more frequent delivery of customer value.

✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

📌 Kubernetes Volume Types

Kubernetes volumes are an integral part of containerized application management, offering various storage options.

➡️ They can be categorized mainly into ephemeral and persistent types.

1️⃣. Ephemeral volumes, like emptyDir, are tied to the pod's lifecycle, providing temporary storage.

2️⃣. Persistent Volumes (PVs), like nfs, offer long-term storage solutions, independent of any single pod's lifecycle.

This flexibility in storage options ensures Kubernetes can handle a wide range of application requirements, from temporary cache storage to long-term data persistence.


🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🔔 Free Resources for End-to-End DevOps ♾ Learning:


🐧 𝗟𝗶𝗻𝘂𝘅:
- The Linux Foundation: https://lnkd.in/epkP5dYQ
- Linux Documentation: https://lnkd.in/eWNYW246
- Fedora Project: fedoraproject.org

🐍 𝗦𝗰𝗿𝗶𝗽𝘁𝗶𝗻𝗴:
- Python: learnpython.org
- Go: go.dev/tour
- Automate with Python: automatetheboringstuff.com
- Golang Bootcamp: https://lnkd.in/eSsK7KUG

🤖 𝗔𝗜 𝗳𝗼𝗿 𝗗𝗲𝘃𝗼𝗽𝘀:
- GenAI - https://brij.guru/ai

🌐 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴:
- Cisco Networking Academy: netacad.com
- Networking Fundamentals: https://lnkd.in/eQ62Bfza
- Networking: A Top-Down Approach: kurose.cslash.net
- FreeCodeCamp's Course: https://lnkd.in/ecAsMH2w

🧑‍💻 𝗚𝗶𝘁:
- Git SCM: git-scm.com
- Try Git: github.com/Try
- Git Tutorials: https://lnkd.in/eDbQBQfD
- Git Interactive Tutorial: https://lnkd.in/eqfE2ZC4

🐳 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿𝘀:
- Docker Documentation: docs.docker.com
- Docker Hub: hub.docker.com
- Docker Labs: dockerlabs.collabnix.com
- Kubernetes Fundamentals: https://lnkd.in/eurRUTSt

☁️ 𝗖𝗹𝗼𝘂𝗱:
- AWS Free Tier: aws.amazon.com/free
- Microsoft Azure Free Account: https://lnkd.in/ehxD777x
- Google Cloud Platform Free Tier: cloud.google.com/free
- Cloud Academy: cloudacademy.com

⚙️ 𝗖𝗜/𝗖𝗗:
- Jenkins: jenkins.io
- Travis CI: https://lnkd.in/eDTJtRjB
- CircleCI: circleci.com
- GitLab CI/CD: docs.gitlab.com/ee/ci

🧩 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻:
- Kubernetes Documentation: kubernetes.io/docs/home
- Kubernetes the Hard Way: https://lnkd.in/edWs7_FW
- CNCF Curriculum: cncf.io
- Kubernetes Fundamentals: https://lnkd.in/e55BRxGy

🔍 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆:
- Prometheus: prometheus.io
- Grafana: grafana.com
- Elasticsearch: elastic.co
- Jaeger: https://lnkd.in/eiFkzXwD

📜 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲 (𝗜𝗮𝗖):
- Terraform: terraform.io
- AWS CloudFormation: https://lnkd.in/e4wGb2eT
- Azure Resource Manager: https://lnkd.in/eWzjg94i
- Deployment Manager: https://lnkd.in/ekAQpT3n

🔏 𝗣𝗼𝗹𝗶𝗰𝘆 𝗮𝘀 𝗖𝗼𝗱𝗲:
- Open Policy Agent: https://lnkd.in/eG4jMZSU
- Kyverno: kyverno.io/docs
- Rego: https://lnkd.in/eD75meCB

🕸 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗠𝗲𝘀𝗵:
- Istio: https://lnkd.in/eaxdAMZC
- Linkerd: linkerd.io
- Consul Service Mesh: https://lnkd.in/eEn3eacn


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

🔥 I have created this handy diagram that breaks down the key concepts of Kafka in a simple and easy-to-understand way.

🔴 𝗣𝗿𝗼𝗱𝘂𝗰𝗲𝗿:

A Kafka producer is an entity that publishes data to topics within the Kafka cluster. In essence, producers are the sources of data streams, which might originate from various applications, systems, or sensors. They push records into Kafka topics, and each record consists of a key, a value, and a timestamp.

🔴 𝗖𝗼𝗻𝘀𝘂𝗺𝗲𝗿:

A Kafka consumer pulls data from Kafka topics to which it subscribes. Consumers process the data and often are part of a consumer group. In a group, multiple consumers can read from a topic in parallel, with each consumer responsible for reading from certain partitions, ensuring efficient data processing.

🔴 𝗧𝗼𝗽𝗶𝗰:

A topic is a category or feed name to which records are published. Topics in Kafka are multi-subscriber; they can be consumed by multiple consumers and consumer groups. Topics are divided into partitions to allow for data scalability and parallel processing.

🔴 𝗣𝗮𝗿𝘁𝗶𝘁𝗶𝗼𝗻:

A topic can be divided into partitions, which are essentially subsets of a topic's data. Each partition is an ordered, immutable sequence of records that is continually appended to. Partitions allow topics to be parallelized by splitting the data across multiple brokers.

🔴 𝗕𝗿𝗼𝗸𝗲𝗿:

A broker is a single Kafka server that forms part of the Kafka cluster. Brokers are responsible for maintaining the published data. Each broker may have zero or more partitions per topic and can handle data for multiple topics.

🔴 𝗖𝗹𝘂𝘀𝘁𝗲𝗿:

A Kafka cluster comprises one or more brokers. The cluster is the physical grouping of one or more brokers that work together to provide scalability, fault tolerance, and load balancing. The Kafka cluster manages the persistence and replication of message data.

🔴 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:

A replica is a copy of a partition. Kafka replicates partitions across multiple brokers to ensure data is not lost if a broker fails. Replicas are classified as either leader replicas or follower replicas.

🔴 𝗟𝗲𝗮𝗱𝗲𝗿 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:

For each partition, one broker is designated as the leader. The leader replica handles all read and write requests for the partition. Other replicas simply copy the data from the leader.

🔴 𝗙𝗼𝗹𝗹𝗼𝘄𝗲𝗿 𝗥𝗲𝗽𝗹𝗶𝗰𝗮:

Follower replicas are copies of the leader replica for a partition. They replicate the leader's log and do not serve client requests. Instead, their purpose is to provide redundancy and to take over as the leader if the current leader fails.

✈️ 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

➡️ Title: DevOps Engineer
➡️ Location: Remote

➡️ Job Description:

1-3 years of exp in DevOps (AWS/ Azure/ GCP).
Hands-on exp in deploying Kubernetes cluster using ELK/ GKE environment.
Creating CI/CD pipeline using Jenkins.
Using Monitoring tools like Prometheus/ Grafana/ Stack driver.
Docker
Infra Automation scripting
➡️ Send resumes/Contact - careers@suesys.com

Remember that time when everyone was like, "Coding? Nah, DevOps is all about automation, CI/CD, blah-blah." Yeah, me too. In 2020, freshman year, convinced myself I could skip "DSA", "messy code" & just focus on DevOps tools. Big mistake. If you are from a Tier 3 college & genuinely want to do good, learn & earn some good bucks, coding & basic computer science knowledge are good to have.

In 2020, there wasn't much content on DevOps (or could be my algo), but there were few solid senior OPS / DevOps folks whom I followed. In recent times, there has been huge content overload, conflicting advice, and enough acronyms to fill a dictionary. If I were to start in 2023, I would've been lost too.

Why I am sharing this? During my freshman year, I used to follow a guy, from whom I got to know about DevOps. He used to say, "Giving back to the community." In my freshman year, I didn't understand what he meant, but now that I do, I want to share this list of free but best resources/bootcamps you can find online.

1️⃣. DevOps Roadmap by Savinder Puri: https://lnkd.in/d-qTThxi

2️⃣. Computer Networks by Kunal Kushwaha: https://lnkd.in/dWmq_ygr && Git/Github tutorial: https://lnkd.in/dGKHzNYg

3️⃣. Docker by Gourav Shah: https://lnkd.in/dKp6bnEA

4️⃣. Playlist of different tools by Kubesimplify / Saiyam Pathak: https://lnkd.in/dWbEP993

5️⃣. Jenkins by Mukesh Otwani: https://lnkd.in/deXCYGkj

6️⃣. Kubernetes by Abhishek Veeramalla: https://lnkd.in/dA6_mtnh

7️⃣. Cloud by ExamPro / Andrew Brown: https://www.exampro.co/

8️⃣. GoLang by Anthony GG: https://lnkd.in/dwVKg8DG


🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

May the pride of being Indian fill your heart with joy and gratitude.

Happy Republic Day to you and your family. 🇮🇳


🛒 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!

😀 10 DevOps Real time Scenarios. 😀
🚀 Issues as well as their resolutions: 🚀

🔢. Continuous Integration Pipeline Failure and its Resolution.
🔗 https://lnkd.in/g9nBb79u

🔢. Application experiences performance degradation and becomes slow during high-traffic periods and its resolution.
🔗 https://lnkd.in/g9nBb79u

🔢. Deployments are error-prone and inconsistent across different environments and its resolution.
🔗 https://lnkd.in/gE6FYcBz

🔢. The application goes down in production due to an unforeseen issue and its resolution.
🔗 https://lnkd.in/gE6FYcBz

🔢. A security vulnerability is discovered in a component of the application stack and its resolution.
🔗 https://lnkd.in/gPtZ9_Ge

🔢. Production environments start to deviate from their desired configurations over time and its resolution.
🔗 https://lnkd.in/gPtZ9_Ge

🔢. A critical service experiences an outage, impacting users and business operations and its resolution.
🔗 https://lnkd.in/gvTtGYC7

🔢. Communication breakdowns between development and operations teams lead to misunderstandings and delays and its resolution.
🔗 https://lnkd.in/gvTtGYC7

🔢. A major release causes unexpected issues in the production environment.
🔗 https://lnkd.in/gYbFKPrv

🔢🔢. Cloud resource costs are increasing beyond budgeted limits.
🔗 https://lnkd.in/gYbFKPrv


🎄 𝗙𝗼𝗹𝗹𝗼𝘄 @prodevopsguy 𝗳𝗼𝗿 𝗺𝗼𝗿𝗲 𝘀𝘂𝗰𝗵 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗮𝗿𝗼𝘂𝗻𝗱 𝗰𝗹𝗼𝘂𝗱 & 𝗗𝗲𝘃𝗢𝗽𝘀!!!